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Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Computed materials data using density functional theory calculations. These calculations determine the electronic structure of bulk materials by solving approximations to the Schrodinger equation. For more information, see https://materialsproject.org/docs/calculations
Hard carbon is regarded as the most promising anode material for commercialization of Na ion batteries because of its high capacity and low cost. At present, the practical utilization of hard carbon anodes is largely limited by the low initial Coulombic efficiency (ICE). Na ions have been found to adopt an adsorption–insertion storage mechanism. In this paper a systematic way to control the defect concentration and porosity of hard carbon with similar overall architectures is shown. This study elucidates that the defects in the graphite layers are directly related to the ICE as they would trap Na ions and create a repulsive electric field for other Na ions so as to shorten the low-voltage intercalation capacity. The obtained low defect and porosity hard carbon electrode has achieved the highest ICE of 86.1% (94.5% for pure hard carbon material by subtracting that of the conductive carbon black), reversible capacity of 361 mA h g-1, and excellent cycle stability (93.4% of capacity retention over 100 cycles). This result sheds light on feasible design principles for high performance Na storage hard carbon: suitable carbon layer distance and defect free graphitic layers.
Lignin decomposition is critically linked to terrestrial carbon (C) cycle due to the enormous C mass of lignin and its importance in controlling overall rates of litter decomposition. Interactions between lignin and iron (Fe) minerals have been increasingly recognized as key mediators of lignin decomposition in experimental studies. However, we still lack a quantitative understanding of how Fe minerals interact with microbes to control lignin decomposition. Here, we leveraged experimental results from an incubation of Fe-rich soil, in which lignin decomposition rates were measured at aerobic conditions after four levels of pre-treated O2 availability, to examine microbe-Fe (MiFe) interactions in lignin decomposition with a MiFe model. We quantified how Fe redox cycling interacted with microbial activities to control lignin decomposition via data-model integration. Our results showed that the MiFe model with time-dependent growth and mortality functions better represented CO2 release from lignin decomposition (R2 ranging from 0.96 to 0.97) than models assuming either first-order or Michaelis-Menten kinetics. Reduction of Fe(III) to Fe(II) after pre-treatments with lower O2 availability stimu-lated the Fenton reaction to break down macro-molecular lignin into small molecules available to microbes. The small molecules of lignin and necromass bounded with oxidized Fe and were protected from decomposition. After 1-year incubation, the model implied that most of C stabilized with Fe minerals was derived from small molecular lignin C. Our quantitative analysis of microbe-Fe interactions sheds new light on lignin decomposition and preservation and helps improve model prediction of soil C persistence under global change.
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Using high-resolution transmission electron microscopy and electron energy-loss spectroscopy, we demonstrate that beryllium oxide crystallizes in the planar hexagonal structure in a graphene liquid cell by a wet-chemistry approach. These liquid cells can feature van-der-Waals pressures up to 1 GPa, producing a miniaturized high-pressure container for the crystallization in solution. The thickness of as-received crystals is beyond the thermodynamic ultra-thin limit above which the wurtzite phase is energetically more favorable according to the theoretical prediction. The crystallization of the planar phase is ascribed to the near-free-standing condition afforded by the graphene surface. Our calculations show that the energy barrier of the phase transition is responsible for the observed thickness beyond the previously predicted limit. These findings open a new door for exploring aqueous-solution approaches of more metal-oxide semiconductors with exotic phase structures and properties in graphene-encapsulated confined cells.
Soil respiration, the major pathway for ecosystem carbon (C) loss, has the potential to enter a positive feedback loop with the atmospheric CO2 due to climate warming. For reliable projections of climate-carbon feedbacks, accurate quantification of soil respiration and identification of mechanisms that control its variability are essential. Process-based models simulate soil respiration as functions of belowground C input, organic matter quality, and sensitivity to environmental conditions. However, evaluation and calibration of process-based models against the long-term in situ measurements are rare. Here, we evaluate the performance of the Terrestrial ECOsystem (TECO) model in simulating total and heterotrophic soil respiration measured during a 16-year warming experiment in a mixed-grass prairie; calibrate model parameters against these and other measurements collected during the experiment; and explore whether the mechanisms of C dynamics have changed over the years. Calibrating model parameters against observations of individual years substantially improved model performance in comparison to pre-calibration simulations, explaining 79–86% of variability in observed soil respiration. Interannual variation of the calibrated model parameters indicated increasing recalcitrance of soil C and changing environmental sensitivity of microbes. Overall, we found that (1) soil organic C became more recalcitrant in intact soil compared to root-free soil; (2) warming offset the effects of increasing C recalcitrance in intact soil and changed microbial sensitivity to moisture conditions. Furthermore, these findings indicate that soil respiration may decrease in the future due to C quality, but this decrease may be offset by warming-induced changes in C cycling mechanisms and their responses to moisture conditions.
Climate warming is leading to greater precipitation variability, resulting in increased frequency and intensity of both drought and wet extremes. However, how these extreme events interact with climate warming and hay-harvest in grasslands to impact ecosystem functions has not yet been well explored. In this study, we took advantage of a long-term experiment to examine how climate warming and clipping (i.e., mimicking hay harvest) regulated impacts of naturally occurring drought and wet extremes on ecosystem CO 2 fluxes of a tallgrass prairie in the Great Plains, USA. Warming resulted in net ecosystem carbon release (i.e., positive net ecosystem CO 2 exchange, NEE) in the extreme drought year of 2011, but significantly enhanced net carbon uptake in the extremely wet year of 2015 in comparison with NEE in normal years. Warming-induced carbon release in the drought year was due to significantly enhanced ecosystem respiration (ER) from mid-summer to early-autumn, whereas warming-enhanced NEE in the wet year was due to an increase in aboveground net primary production (ANPP) compared to those in normal years. Drought diminished warming-induced increases in ANPP to about one sixth of that in the wet year in the unclipped plots. Interestingly, clipping offset the drought-mediated ecosystem carbon loss by increasing GPP and weakened the wet-enhanced ANPP. Altogether, our results suggest that a future, warmer climate may exacerbate carbon losses in terrestrial ecosystems during drought extremes but stimulate the ecosystem carbon sink under wet extremes.
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Quantifying the ecological patterns of loss of ecosystem function in extreme drought is important to understand the carbon exchange between the land and atmosphere. Rain-use efficiency [RUE; gross primary production (GPP)/precipitation] acts as a typical indicator of ecosystem function. Here in this study, a novel method based on maximum rain-use efficiency (RUE max ) was developed to detect losses of ecosystem function globally. Three global GPP datasets from the MODIS remote sensing data (MOD17), ground upscaling FLUXNET observations (MPI-BGC), and process-based model simulations (BESS), and a global gridded precipitation product (CRU) were used to develop annual global RUE datasets for 2001–2011. Large, well-known extreme drought events were detected, e.g. 2003 drought in Europe, 2002 and 2011 drought in the U.S., and 2010 drought in Russia. Our results show that extreme drought-induced loss of ecosystem function could impact 0.9% ± 0.1% of earth's vegetated land per year and was mainly distributed in semi-arid regions. The reduced carbon uptake caused by functional loss (0.14 ± 0.03 PgC/yr) could explain >70% of the interannual variation in GPP in drought-affected areas (p ≤ 0.001). Our results highlight the impact of ecosystem function loss in semi-arid regions with increasing precipitation variability and dry land expansion expected in the future.
Metallization of quantum spin liquid (QSL) materials has long been considered as a potential route toward unconventional superconductivity. Here, we investigate the pressurization of lithium ytterbium diselenide (LiYbSe 2 ), a three-dimensional QSL candidate with a pyrochlore structure. High-pressure X-ray diffraction (up to 15 GPa) and Raman spectroscopy (up to 48 GPa) reveal no significant structural changes within this pressure range. Remarkably insulating, LiYbSe 2 exhibits a resistance below 10 5 Ω only at pressures exceeding 25 GPa, accompanied by a gradual reduction of band gap upon compression. Interestingly, an insulator-to-metal transition occurs around 68 GPa, and the metallic behavior persists up to 123.5 GPa, the highest pressure achieved in this study. A possible sign of magnetic transitions is also observed. The insulator-to-metal transition in LiYbSe 2 under high pressure presents an ideal platform to explore the pressure effects on QSL candidates of spin-1/2 Yb 3+ systems with various lattice patterns.
Here, the absorption spectra of acetylene (HCCH) and vinylidene (H 2 CC) as well as their deuterated isotopologues are investigated theoretically on a near spectroscopically accurate full-dimensional potential energy surface reported in an earlier publication, using dipole moment surfaces reported in this work, which are constructed with a neural network method from a large number of ab initio data points. These global surfaces cover not only the deep acetylene well, but also the vinylidene well, as well as the transition region between the two isomers. The agreement with available experimental data for acetylene is excellent, validating both the potential energy surface and the dipole moment surfaces. The infrared spectra of vinylidene and its deuterated isotopologues are predicted. The potential and dipole moment surfaces lay the foundation for future spectroscopic studies of the acetylene-vinylidene isomerization involving large amplitude motions.
In van der Waals (vdW) heterostructures, the interlayer electron–phonon coupling (EPC) provides one unique channel to nonlocally engineer these elementary particles. However, limited by the stringent occurrence conditions, the efficient engineering of interlayer EPC remains elusive. Here we report a multitier engineering of interlayer EPC in WS2/boron nitride (BN) heterostructures, including isotope enrichments of BN substrates, temperature, and high-pressure tuning. The hyperfine isotope dependence of Raman intensities was unambiguously revealed. In combination with theoretical calculations, we anticipate that WS2/BN supercells could induce Brillouin-zone-folded phonons that contribute to the interlayer coupling, leading to a complex nature of broad Raman peaks. We further demonstrate the significance of a previously unexplored parameter, the interlayer spacing. By varying the temperature and high pressure, we effectively manipulated the strengths of EPC with on/off capabilities, indicating critical thresholds of the layer–layer spacing for activating and strengthening interlayer EPC. Our findings provide new opportunities to engineer vdW heterostructures with controlled interlayer coupling.
We report the physical properties of copper oxide high-temperature superconductors have been studied extensively, such as its band structure, and doping effects of Bi 2 Sr 2 CaCu 2 O 8+δ (Bi-2212). However, some chemical-related properties of these superconductors are rarely reported, such as their stability in air. Here, we report experiments combined with ab initio calculations that address the effects of water in contact with Bi-2212. The evolution of Bi-2212 flake with exposure to water for different time intervals were tested and characterized by optical microscopy (OM), atomic force microscopy (AFM), Raman spectroscopy, transmission electron microscopy (TEM) and electrical measurements. The thickness of Bi-2212 flakes is gradually decreased in water, and some thin flakes can be completely etched away after a few days. The stability of Bi-2212 in other solvents is also evaluated, including alcohol, acetone, HCl and KOH. The morphology of Bi-2212 flakes is relatively stable in organic solvents. However, the flakes are etched relatively quick in HCl and KOH, especially in acidic environment. Our results imply that hydrogen ion is primarily responsible for the deterioration of their properties. Both TEM and calculation results demonstrate that the atoms in Bi-O plane is relatively stable when compared to the inner atoms in Sr-O, Ca-O and Cu-O planes. This work contributes towards understanding the chemical stability of Bi-2212 superconducting device in environmental medium, which is important for both fundamental studies and practical applications of copper oxide high-temperature superconductors.
The dynamics of soil phosphorus (P) control its bioavailability. Yet it remains a challenge to quantify soil P dynamics. In this work we developed a soil P dynamics (SPD) model. We then assimilated eight data sets of 426-day changes in Hedley P fractions into the SPD model, to quantify the dynamics of six major P pools in eight soil samples that are representative of a wide type of soils. The performance of our SPD model was better for labile P, secondary mineral P, and occluded P than for nonoccluded organic P (Po) and primary mineral P. All parameters describing soil P dynamics were approximately constrained by the data sets. The average turnover rates were labile P 0.040 g g -1 day-1, nonoccluded Po 0.051 g g -1 day -1 , secondary mineral P 0.023 g g -1 day -1 , primary mineral P 0.00088 g g -1 day -1 , occluded Po 0.0066 g g -1 day -1 , and occluded inorganic P 0.0065 g g -1 day -1 , in the greenhouse environment studied. Labile P was transferred on average more to nonoccluded Po (transfer coefficient of 0.42) and secondary mineral P (0.38) than to plants (0.20). Soil pH and organic C concentration were the key soil properties regulating the competition for P between plants and soil secondary minerals. The turnover rate of labile P was positively correlated with that of nonoccluded Po and secondary mineral P. The pool size of labile P was most sensitive to its turnover rate. Overall, we suggest data assimilation can contribute significantly to an improved understanding of soil P dynamics.
Land ecosystems contribute to climate change mitigation by taking up approximately 30% of anthropogenically emitted carbon. However, estimates of the amount and distribution of carbon uptake across the world's ecosystems or biomes display great uncertainty. The latter hinders a full understanding of the mechanisms and drivers of land carbon uptake, and predictions of the future fate of the land carbon sink. The latter is needed as evidence to inform climate mitigation strategies such as afforestation schemes. To advance land carbon cycle modeling, we have developed a matrix approach. Land carbon cycle models use carbon balance equations to represent carbon exchanges among pools. Our approach organizes this set of equations into a single matrix equation without altering any processes of the original model. The matrix equation enables the development of a theoretical framework for understanding the general, transient behavior of the land carbon cycle. While carbon input and residence time are used to quantify carbon storage capacity at steady state, a third quantity, carbon storage potential, integrates fluxes with time to define dynamic disequilibrium of the carbon cycle under global change. The matrix approach can help address critical contemporary issues in modeling, including pinpointing sources of model uncertainty and accelerating spin-up of land carbon cycle models by tens of times. The accelerated spin-up liberates models from the computational burden that hinders comprehensive parameter sensitivity analysis and assimilation of observational data to improve model accuracy. Such computational efficiency offered by the matrix approach enables substantial improvement of model predictions using ever-increasing data availability. Overall, the matrix approach offers a step change forward for understanding and modeling the land carbon cycle.
Abstract Land use change (LUC) alters the global carbon (C) stock, but our estimation of the alteration remains uncertain and is a major impediment to predicting the global C cycle. The uncertainty is partly due to the limited number and geographical bias of observations, and limited exploration of its predictors. Here we generated a comprehensive global database of 5,980 observations from 790 articles. The number of sites evaluated is at least seven times larger than in previous meta‐analyses. Our constrained estimates of different LUC's effects on soil organic C (SOC) and their variations across global climates reveal underestimation/overestimation in previous estimates. Converting forests and grasslands to croplands reduced SOC by 24.5% ± 1.53% (−11.03 ± 1.06 Mg ha −1 ) and 22.7% ± 1.22% (−8.09 ± 0.67 Mg ha −1 ), while 28.0% ± 1.56% (4.46 ± 0.42 Mg ha −1 ) and 33.5% ± 1.68% (5.8 ± 0.38 Mg ha −1 ) increases, respectively, were obtained in the reverse processes. Converting forests to grasslands decreased SOC by 2.1% ± 1.22% (−1.13 ± 0.44 Mg ha −1 ), while the reverse process increased SOC by 18.6% ± 1.73% (3.31 ± 0.51 Mg ha −1 ). Modeled relative importance of 10 drivers of LUC's impact on SOC revealed that higher initial SOC (iSOC) does not solely determine SOC loss in SOC‐negative LUC scenarios as previously proposed. Across four decades, reconverting croplands to forests and grasslands recovered only 49.5% (6.1 ± 0.51 Mg ha −1 ) and 75.3% (7.0 ± 0.38 Mg ha −1 ) of the iSOC, respectively, indicating the need for protecting C‐rich ecosystems. Our global data set advances information on LUC's effect on SOC and can be valuable to constrain Earth system models to reliably estimate global SOC stocks and plan climate change mitigation strategies.